Estratégias operatórias para a colheita mecanizada de cana-de-açúcar: contribuições para o desempenho

• Ano de defesa: 2020
• Autor(a) principal: Freitas, Larissa Diniz
• Orientador(a): Menegon, Nilton Luiz
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia de Produção - PPGEP
• Palavras-chave em Português: Ergonomia; Curso da ação; Mecanização agrícola; Colhedoras
• Palavras-chave em Inglês: Ergonomics; Course of action; Agricultural mechanization; Harvesters
• Área do conhecimento CNPq: ENGENHARIAS::ENGENHARIA DE PRODUCAO::GERENCIA DE PRODUCAO; ENGENHARIAS::ENGENHARIA DE PRODUCAO::ENGENHARIA DO PRODUTO::ERGONOMIA
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/13188

Introduction - The current production rates of the mechanized sugarcane harvest, below those expected at the beginning of the mechanization process, motivate countless researchers to make several quantitative methodological attempts in the different dimensions of the activity, in order to understand how the variables of the mechanized cutting process are correlated and how they interfere in the performance of the harvesting equipment. However, from a speech by a harvester operator: “It is the cane that shows the ability for you to walk”, the intelligence of the worker's practice in his/her activity is revealed, showing his/her fundamental role in the operational performance through his/her reading of the cane field. Objective - Evaluate how the technocentric and quantitative variables used in the calculation of the global efficiency of the sugarcane harvester are influenced by the operator's action, from the perspective of the ergonomics of the activity. Methods - Qualitative research, the main results of which were assessed through the Work Analysis of the sugarcane harvester operators under the Course of Action ergonomic method. Triangulation (observations and interviews) was used as data collection procedures. Twenty visits were made to the work teams of a sugar-energy plant, in which 17 were carried out on the sugarcane cutting and loading work team and the other three on the teams of fertigation, fertilization, planting and harvesting of seedlings, on different days of the week, in different shifts, varying between 2 to 9 hours in duration. On each visit to the cutting teams, an operator was accompanied during his/her work shift, from inside the harvester's cabin. Workers' courses of action were recorded in chronicles and then analyzed in graphs of tetradic signs. Results - The analysis of the courses of action revealed an operational logic that is imposed on workers by mechanization and, at the same time, hidden by the productive indexes. The operator perceives the context of his/her own work and the work of his/her colleagues to make decisions, prioritizing sometimes the cleanliness of the harvested mass, the fuel consumption, the losses of cane in the field and the loading flow in the transshipment; sometimes, the harvesting strategy, the number of maneuvers, the maintenance of the implements and the release of overflows. This prioritization of actions directly affects performance indicators, which can be calculated using the data indicated by monitoring software. Despite this, the OEE was not shown to be sufficient to evaluate the performance in mechanized harvesting, due to the limitation and loss of data; the extrapolation of what would be the active time; the disregard for the sugarcane productivity; and, the failure to contemplate the real conditions of the harvesting equipment and, not even, the operating strategies that the operators are submitted to develop to create satisfactory indicators for the plant. Conclusion - Because of the partial availability of the harvester, where problems coexist throughout the harvesting process, and because of the instability in the production of cane cultivation, which has variability that automation does not master, the operator is asked to use his skills to do your job. And, therefore, the greater this competence, the greater the possibilities for action to generate better indicators.